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Models for Spatially Dependent Missing Data

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  • James P. LeSage

    ()

  • R. Kelley Pace

    ()

Abstract

Most hedonic pricing studies using transaction data employ only sold properties. Since the properties sold during any year or even decade represent only a fraction of all properties, this approach ignores the potentially valuable information content of unsold properties which have known characteristics. In fact, explanatory variable information on house characteristics for all properties, sold and unsold, are often available from assessors. We set forth an estimation approach that predicts missing values of the dependent variable when the sample data exhibit spatial dependence. Employing information on the housing characteristics of both sold and unsold properties can improve prediction, increase estimation efficiency for the missing-at-random case, and reduce self-selection bias in the non-missing-at-random case. We demonstrate these advantages with a Monte Carlo experiment as well as with actual housing data.

Suggested Citation

  • James P. LeSage & R. Kelley Pace, 2004. "Models for Spatially Dependent Missing Data," The Journal of Real Estate Finance and Economics, Springer, vol. 29(2), pages 233-254, September.
  • Handle: RePEc:kap:jrefec:v:29:y:2004:i:2:p:233-254
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    Citations

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    Cited by:

    1. Jorge Chica-Olmo, 2007. "Prediction of Housing Location Price by a Multivariate Spatial Method: Cokriging," Journal of Real Estate Research, American Real Estate Society, vol. 29(1), pages 95-114.
    2. Catherine Baumont, 2009. "Spatial effects of urban public policies on housing values," Papers in Regional Science, Wiley Blackwell, vol. 88(2), pages 301-326, June.
    3. Wolfgang Polasek & Richard Sellner, 2008. "Spatial Chow-Lin Methods: Bayesian And Ml Forecast Comparisons," Working Paper series 38_08, Rimini Centre for Economic Analysis.
    4. repec:spr:anresc:v:60:y:2018:i:1:d:10.1007_s00168-015-0737-2 is not listed on IDEAS
    5. Seya, Hajime & Yamagata, Yoshiki & Tsutsumi, Morito, 2013. "Automatic selection of a spatial weight matrix in spatial econometrics: Application to a spatial hedonic approach," Regional Science and Urban Economics, Elsevier, vol. 43(3), pages 429-444.
    6. Lee, Lung-fei & Yu, Jihai, 2015. "Estimation of fixed effects panel regression models with separable and nonseparable space–time filters," Journal of Econometrics, Elsevier, vol. 184(1), pages 174-192.
    7. Xiaowen Dai & Libin Jin & Anqi Shi & Lei Shi, 2016. "Outlier detection and accommodation in general spatial models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 25(3), pages 453-475, August.
    8. José-María Montero-Lorenzo & Beatriz Larraz-Iribas & Antonio Páez, 2009. "Estimating commercial property prices: an application of cokriging with housing prices as ancillary information," Journal of Geographical Systems, Springer, vol. 11(4), pages 407-425, December.
    9. Harry Kelejian & Ingmar Prucha, 2010. "Spatial models with spatially lagged dependent variables and incomplete data," Journal of Geographical Systems, Springer, vol. 12(3), pages 241-257, September.
    10. E.-H. Yoo & P. Kyriakidis, 2009. "Area-to-point Kriging in spatial hedonic pricing models," Journal of Geographical Systems, Springer, vol. 11(4), pages 381-406, December.
    11. Richard Arnott & Huiling Zhang, 2015. "The Aggregate Value of Land in the Greater Los Angeles Region," Working Papers 201506, University of California at Riverside, Department of Economics.
    12. Takafumi Kato, 2008. "A Further Exploration Into The Robustness Of Spatial Autocorrelation Specifications," Journal of Regional Science, Wiley Blackwell, vol. 48(3), pages 615-639.
    13. Masha Maslianskaia-Pautrel & Marc Baudry, 2012. "Revisiting the hedonic price method to assess the implicit price of environmental quality with market segmentation," Working Papers hal-00759247, HAL.
    14. Alicia N. Rambaldi & D.S. Prasada Rao & K. Renuka Ganegodage, 2009. "Spatial Autocorrelation and Extrapolation of Purchasing Power Parities. Modelling and Sensitivity Analysis," CEPA Working Papers Series WP012009, School of Economics, University of Queensland, Australia.
    15. repec:eee:csdana:v:120:y:2018:i:c:p:98-110 is not listed on IDEAS
    16. Bin Zhou & Kara Kockelman, 2008. "Neighborhood impacts on land use change: a multinomial logit model of spatial relationships," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(2), pages 321-340, June.
    17. Wang, Wei & Lee, Lung-fei, 2013. "Estimation of spatial panel data models with randomly missing data in the dependent variable," Regional Science and Urban Economics, Elsevier, vol. 43(3), pages 521-538.
    18. Antonio Páez, 2009. "Recent research in spatial real estate hedonic analysis," Journal of Geographical Systems, Springer, vol. 11(4), pages 311-316, December.
    19. Shuang Zhu & R. Pace, 2014. "Modeling Spatially Interdependent Mortgage Decisions," The Journal of Real Estate Finance and Economics, Springer, vol. 49(4), pages 598-620, November.
    20. Bing Zhu & Roland Füss & Nico Rottke, 2011. "The Predictive Power of Anisotropic Spatial Correlation Modeling in Housing Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 42(4), pages 542-565, May.
    21. Bernard Fingleton, 2009. "Prediction Using Panel Data Regression with Spatial Random Effects," International Regional Science Review, , vol. 32(2), pages 195-220, April.
    22. Takafumi Kato, 2013. "Usefulness of the Information Contained in the Prediction Sample for the Spatial Error Model," The Journal of Real Estate Finance and Economics, Springer, vol. 47(1), pages 169-195, July.
    23. Kato, Takafumi, 2012. "Prediction in the lognormal regression model with spatial error dependence," Journal of Housing Economics, Elsevier, vol. 21(1), pages 66-76.
    24. Olivier Parent & Rainer Hofe, 2013. "Understanding the impact of trails on residential property values in the presence of spatial dependence," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 51(2), pages 355-375, October.

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